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AdaBoost-based Real-Time Face Detection & Tracking System

AdaBoost 기반의 실시간 고속 얼굴검출 및 추적시스템의 개발

  • 김정현 (부산대학교 기계공학부) ;
  • 김진영 (동명대학교 메카트로닉스공학과) ;
  • 홍영진 (동명대학교 전기전자공학과) ;
  • 권장우 (동명대학교 컴퓨터공학과) ;
  • 강동중 (부산대학교 기계공학부) ;
  • 노태정 (동명대학교 메카트로닉스공학과)
  • Published : 2007.11.01

Abstract

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

Keywords

References

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